CN108920564B - Talent management method based on block chain and terminal thereof - Google Patents
Talent management method based on block chain and terminal thereof Download PDFInfo
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Abstract
The embodiment of the invention discloses a talent growth management method based on a block chain and a terminal thereof, wherein the method comprises the following steps: constructing a knowledge system database, a knowledge note database and a knowledge note comment database based on a block chain technology; performing professional skill evaluation on the individual according to the database to obtain professional skill evaluation data; constructing a talent growth plan database based on the block chain; acquiring talent personal information data, and constructing talent resume metadata according to the talent personal information data, a talent growth plan database and occupational skill evaluation data; and constructing the talent resume according to the talent creation seed Hash and the talent resume metadata. In the embodiment, metadata, knowledge note data, knowledge note comment data, professional skill assessment, talent resume and the like of a knowledge system are recorded on the block chain, talent management such as professional skill assessment, talent resume construction and the like is realized based on the block chain technology, and non-tamper-proof property and authority of data are ensured.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a talent management method based on a block chain and a terminal thereof.
Background
In modern society, different talents are required for different posts in order to maximize the value of talents. Therefore, it is important to manage the growth of talents. In the existing talent management process, for recruitment, the data provided for the recruiter is easy to be tampered by the outside due to the construction and storage modes of the data, and the like, and the data is lack of authority.
Disclosure of Invention
The embodiment of the invention aims to provide a regional chain-based talent growth management method and a terminal thereof, which are used for realizing talent management such as professional skill assessment, talent resume construction and the like based on a regional chain technology and ensuring the non-tamper property and authority of data.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides a talent growth management method based on a blockchain, including:
constructing a knowledge system database, a knowledge note database and a knowledge note comment database based on a block chain technology;
performing professional skill evaluation on the individual according to the knowledge system database, the knowledge note database and the knowledge note evaluation database to obtain professional skill evaluation data;
constructing a talent growth plan database based on the block chain;
acquiring talent personal information data, and constructing talent resume metadata according to the talent personal information data, a talent growth plan database and occupational skill evaluation data;
and constructing the talent resume according to the talent creation seed Hash and the talent resume metadata.
As a preferred embodiment of the present application, the building of the knowledge system database based on the block chain technology specifically includes:
acquiring a discipline Hash, and taking the discipline Hash as discipline metadata;
building a discipline knowledge database according to the discipline metadata, wherein the discipline knowledge database comprises different disciplines, and the different disciplines comprise different versions and different failed advanced paths;
defining the Hash of each discipline element node as a knowledge system creation Hash of a corresponding knowledge system;
and constructing the knowledge system database according to the Hash created by the knowledge system and different advanced paths.
As a preferred embodiment of the present application, constructing a discipline knowledge database according to the discipline metadata specifically includes:
the discipline meta-creation node Hash is discipline meta-data + discipline creation Hash, the second element node Hash is discipline Hash + discipline meta-creation node Hash, the third element node Hash is discipline Hash + second element node Hash, and so on.
As a preferred embodiment of the present application, the constructing the knowledge system database according to the Hash of the creation of the knowledge system and different advanced paths specifically includes:
the Hash is created by a first element node Hash which is the path first-order knowledge system data Hash and a knowledge system, the Hash is created by a second element node Hash which is the path second-order knowledge system data Hash and the first element node Hash, the Hash is created by a third element node Hash which is the path third-order knowledge system data Hash and the second element node Hash, and the like.
As a preferred embodiment of the present application, the building of the knowledge note database based on the block chain technology specifically includes:
acquiring a knowledge note creation Hash and a note data Hash, wherein the knowledge note creation Hash is a meta-node Hash of each advanced knowledge system, and the note data Hash is knowledge note content;
constructing the knowledge note database according to the knowledge note creation Hash and the note data Hash, and specifically comprising the following steps:
the method comprises the steps that a first element node Hash is equal to a note data Hash and a knowledge note creation Hash, a second element node Hash is equal to a note data Hash and a first element node Hash, a third element node Hash is equal to a note data Hash and a second element node Hash, and the like.
As a preferred embodiment of the present application, the method for constructing the knowledge note comment database based on the block chain technology specifically includes:
acquiring a knowledge note comment creation Hash and a note comment data Hash, wherein the knowledge note comment creation Hash is a Hash of each knowledge note meta node, and the note comment data Hash is knowledge note comment data;
constructing the knowledge note comment database according to the knowledge note comment creation Hash and the note comment data Hash, wherein the method specifically comprises the following steps:
the method comprises the steps that a Hash is created by combining a note evaluation data Hash and a knowledge note evaluation, a second element node Hash is created by combining a note evaluation data Hash and a first element node Hash, a third element node Hash is created by combining a note evaluation data Hash and a second element node Hash, and the like.
As a preferred embodiment of the present application, the method further comprises:
and building a knowledge note and a learning record of a knowledge system based on the block chain.
As a preferred embodiment of the present application, constructing a knowledge note based on a block chain specifically includes:
acquiring professional evaluation knowledge note creation Hash and note metadata Hash, wherein the professional evaluation knowledge note creation Hash is metadata for each professional skill evaluation, the metadata for each professional skill evaluation is obtained according to a knowledge system database, a knowledge note database and a knowledge note comment database, and the note metadata Hash is knowledge note content;
constructing a knowledge note according to the occupational evaluation knowledge note creation Hash and the note metadata Hash, and specifically comprising the following steps:
the method comprises the steps that a first meta-node Hash is equal to a note metadata Hash and an occupation evaluation knowledge note creation Hash, a second meta-node Hash is equal to a note metadata Hash and a first meta-node Hash, a third node Hash is equal to a note metadata Hash and a second node Hash, and the like.
As a preferred embodiment of the present application, the building of the learning record of the knowledge system based on the blockchain specifically includes:
acquiring a knowledge Hash of first learning and a new knowledge system Hash;
establishing a learning record of the knowledge system according to the knowledge Hash learned for the first time and the new knowledge system Hash, which specifically comprises the following steps:
and taking the knowledge Hash learned for the first time as a first element node Hash, wherein the second element node Hash is the new knowledge system Hash + the first element node Hash, the third element node Hash is the new knowledge system Hash + the second element node Hash, and so on.
In a second aspect, an embodiment of the present invention further provides a regional chain-based talent growth management terminal, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, where the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method according to the first aspect.
The block chain-based talent growth management method and the terminal thereof are implemented, a knowledge system database, a knowledge note comment database and a talent growth plan database are built based on a block chain technology, professional skill evaluation and talent resume metadata construction are carried out based on the databases, and a talent resume is constructed according to talent creation seed Hash and talent resume metadata; in the embodiment, metadata, knowledge note data, knowledge note comment data, professional skill assessment, talent resume and the like of a knowledge system are recorded on the block chain, talent management such as professional skill assessment, talent resume construction and the like is realized based on the block chain technology, and non-tamper-proof property and authority of data are ensured.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a schematic flowchart of a talent growth management method based on block chains according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a talent growth management terminal based on a block chain according to a first embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, a flowchart of a talent growth management method based on block chains according to a first embodiment of the present invention is shown, where the method includes the following steps:
s101, constructing a knowledge system database, a knowledge note database and a knowledge note comment database based on a block chain technology.
The method for constructing the knowledge system database based on the block chain technology specifically comprises the following steps:
acquiring a discipline Hash, and taking the discipline Hash as discipline metadata;
building a discipline knowledge database according to the discipline metadata, wherein the discipline knowledge database comprises different disciplines, and the different disciplines comprise different versions and different failed advanced paths;
defining the Hash of each discipline element node as a knowledge system creation Hash of a corresponding knowledge system;
and constructing the knowledge system database according to the Hash created by the knowledge system and different advanced paths.
Specifically, the discipline and its basic information (name + author + time, etc.) Hash value (discipline Hash) is used as the node data (discipline metadata) of the discipline information, and the generative knowledge system source data node (discipline generative Hash: a fixed Hash) is added to obtain the generative metadata node (discipline meta-generative node Hash) of the knowledge system, so that the discipline meta-generative node Hash is discipline Hash + discipline generative Hash. The second element node Hash is disciplinary Hash and element creation node Hash; and the third element node Hash is the discipline Hash plus the second element node Hash, and the rest is done in the same way to form a discipline knowledge database. In this manner, a change in the data of any one metanode may affect a change in the data of subsequent associated nodes. Wherein the basic data of the node data is stored in the database.
Furthermore, the knowledge discipline meta-node Hash is used as a source creation node (knowledge system creation Hash) of the corresponding knowledge system. Defining several subject system versions, wherein different versions are suitable for different user groups, different subject system versions have different step routes, and each step content (various information: knowledge abstract and the like, and knowledge system metadata) on a path is taken as node data (knowledge system data Hash). Then the first element node Hash is the path first-order knowledge system data Hash + knowledge system creation Hash, and the second element node Hash is the path second-order knowledge system data Hash + first element node Hash; and the third element node Hash is the path third advanced knowledge system data Hash + the second element node Hash, and the like. In this manner, a change in the data of any one metanode may affect a change in the data of subsequent associated nodes. Wherein the specific advanced knowledge data is stored in a database.
It should be noted that various kinds of knowledge can be organized and framed using the knowledge system. The knowledge system based on the block chain is characterized in that a system framework of the knowledge system is built on the block chain, and metadata (knowledge) of the knowledge system is stored on the block chain, so that the non-tamper property and authority of the data are ensured.
The method comprises the following steps of constructing a knowledge note database based on a block chain technology, and specifically comprises the following steps:
acquiring a knowledge note creation Hash and a note data Hash, wherein the knowledge note creation Hash is a meta-node Hash of each advanced knowledge system, and the note data Hash is knowledge note content;
and constructing the knowledge note database according to the knowledge note creation Hash and the note data Hash.
Specifically, a Hash (knowledge note creation Hash) is created by taking each advanced knowledge system meta-node Hash as a knowledge note source, and knowledge note contents are knowledge note data (contents, time and the like, note metadata Hash). Then the Hash of the first meta-node Hash is equal to the Hash of the note data Hash + the Hash of the knowledge note creation, the Hash of the second meta-node Hash is equal to the Hash of the note data Hash + the Hash of the first meta-node, the Hash of the third meta-node Hash is equal to the Hash of the note data Hash + the Hash of the second meta-node, and so on. In this manner, a change in the data of any one metanode may affect a change in the data of subsequent associated nodes. Wherein the specific knowledge note content data is stored in a database.
The method comprises the following steps of constructing a knowledge note comment database based on a block chain technology, and specifically comprises the following steps:
acquiring a knowledge note comment creation Hash and a note comment data Hash, wherein the knowledge note comment creation Hash is a Hash of each knowledge note meta node, and the note comment data Hash is knowledge note comment data;
and constructing the knowledge note comment database according to the knowledge note comment creation Hash and the note comment data Hash.
Specifically, each knowledge note meta node Hash is used as a knowledge note evaluation source creation Hash (knowledge note evaluation creation Hash), and knowledge note evaluation contents are knowledge note evaluation data (contents, evaluation, time and the like, note evaluation meta data Hash). And then the first element node Hash is the note evaluation data Hash + the knowledge note evaluation creates Hash, the second element node Hash is the note evaluation data Hash + the first element node Hash, the third element node Hash is the note evaluation data Hash + the second element node Hash, and so on. In this manner, a change in the data of any one metanode may affect a change in the data of subsequent associated nodes. Wherein, the specific knowledge note comment content data is stored in the database.
And S102, evaluating the professional skills of the individual according to the knowledge system database, the knowledge note database and the knowledge note evaluation database to obtain professional skill evaluation data.
The following will describe the occupational skills assessment section:
first, the basis for evaluating occupational skills
(1) The professional skill evaluation data corresponding to a person is the comprehensive evaluation of the knowledge system, the knowledge notes and the comments corresponding to the knowledge notes.
(2) The knowledge system is divided into different versions, different weight scores are set for the different versions, the weight scores of metadata of the different knowledge systems are inconsistent, and corresponding values are determined according to the weights. For example, the weight ratio of the primary version is divided into 10 points, the middle-level version is divided into 50 points, the advanced version is divided into 100 points, and the like. According to the stage content of the knowledge system, the learning progress of each person is different, the obtained corresponding system scores are different, and finally the score of the learning progress corresponding to a certain version of the knowledge system is obtained.
(3) The knowledge notes supplement the learning of the content of the knowledge system, and the values of the note content corresponding to different knowledge system versions and stages are different, for example, the value of the note content corresponding to the primary version is 10 points, the value of the note content corresponding to the intermediate version is 50 points, the value of the note content corresponding to the advanced version is 100 points, and the like. The specific value measurement is based on the point evaluation quantity (quantity and quality) of the knowledge note and the value of each knowledge point evaluation, so that the corresponding value of the knowledge note is determined according to the number of scores obtained by the last knowledge note.
Second, professional skill assessment details
(1) Talent data: personal information (name, identity card and the like) of each person serves as personal talent node data (talent Hash), each person has a completely different talent-derived creation seed Hash (talent creation seed Hash), and the combination of the personal information and the identity card forms the talent creation data (talent creation Hash) of each person. Namely, the talent creating Hash is the talent Hash plus the talent creating seed Hash; the Hash created by each talent is independent.
(2) Professional skill assessment: the talent creation Hash of each person is used as a creation Hash (occupational skill assessment creation Hash) of a source of personal occupational skill assessment, and is recorded in talent data of each talent in a chained mode according to a knowledge system learned by each talent, knowledge notes and assessment data of the knowledge notes, wherein each record is metadata for the occupational skill assessment. That is, the professional skill assessment data corresponding to a person is the comprehensive assessment of the knowledge system, the knowledge notes and the comments corresponding to the knowledge notes. After a new knowledge system is learned, corresponding knowledge system data Hash (knowledge Hash) is recorded in a knowledge system learned by a talent, the knowledge Hash learned for the first time is used as a first element node Hash, a second element node Hash is the new knowledge system Hash plus the first element node Hash, a third element node Hash is the new knowledge system Hash plus the second element node Hash, and the rest is done by analogy, so that a complete knowledge system learning record corresponding to a certain person is obtained. The knowledge note takes metadata of each professional skill evaluation as a source creation Hash (professional evaluation knowledge note creation Hash), a first meta node Hash is note metadata Hash + professional evaluation knowledge note creation Hash, a second meta node Hash is note metadata Hash + first meta node Hash, a third meta node Hash is note metadata Hash + second meta node Hash, and so on.
S103, constructing a talent growth plan database based on the block chain.
Specifically, talent stage growth data are acquired, a talent growth seed Hash is used as a source to create a Hash (talent growth and creation Hash), each person has a different talent growth plan data chain, a first element node Hash is a talent growth and creation Hash + a first stage metadata Hash, a second element node Hash is a second stage metadata Hash + a first element node Hash, a third element node Hash is a third stage metadata Hash + a second element node Hash, and so on, so that a talent growth plan database is constructed.
And S104, acquiring personal information data of talents, and constructing the biographical calendar metadata according to the personal information data of talents, the talent growth plan database and the professional skill evaluation data.
And S105, constructing the talent resume according to the talent creation seed Hash and the talent resume metadata.
Specifically, the seed Hash of talent creation is used as the source creation Hash (talent resume creation Hash), each person has a different talent resume chain, the first element node Hash equals to the talent resume creation Hash + the first-stage metadata Hash, the second element node Hash equals to the second-stage metadata Hash + the first element node Hash, the third element node Hash equals to the third-stage metadata Hash + the second element node Hash, and so on.
It should be noted that in the professional skill evaluation of the embodiment, the learning achievement is rated through the learning of the knowledge system and the public evaluation of the corresponding learning achievement, such as the learning record and the learning note, and the professional skill level of the talent is determined according to the result, and the final skill level result and the evaluation process are recorded on the block chain, so that the non-tamper property and the authority of the data are ensured. In addition, the result of determining the corresponding professional skill level of the talent through the professional skill assessment based on the block chain is stored on the block chain, so that the non-tamper property and the authority of the growth data of the talent are ensured, and the talent recruitment service of the enterprise is guided by the data.
Further, the application of occupational skills assessment and growth management is described as follows:
(1) the talent data comprises professional planning and professional selection contents of each person, according to the professional planning and selection, the embodiment of the invention designs targeted professional planning contents, and records the data (talent stage growth metadata) of each stage in the corresponding talent growth plan.
(2) After the growth plan of talents is determined, corresponding knowledge system data is accessed according to the talent stage growth metadata, the skill condition of the talents, namely professional skill evaluation, is evaluated according to the learning progress of the talents, the capability level of the talents is determined according to corresponding learning scores, and the capability level is recorded in a talent resume.
(3) And classifying and grading talents by using talent vocational planning and vocational selection contents in the talent data, providing talent data sources for enterprise recruitment services by using the classified talent data, and determining the skill level of the corresponding talents according to vocational skill evaluation results (scores).
In summary, referring to fig. 2, by implementing the method for talent growth management based on block chains provided by the embodiment of the present invention, metadata of a knowledge system, knowledge note data, knowledge note comment data, professional skill assessment, talent resume, and the like are recorded on the block chains, so that talent management such as professional skill assessment, talent resume construction, and the like is implemented based on the block chain technology, and thus, the non-tamper-ability and authority of data are ensured.
Correspondingly, on the basis of the talent growth management method based on the block chain provided in the above embodiment, the embodiment of the present invention further provides a talent growth management terminal based on the block chain. Referring to fig. 3, the talent growth management terminal based on block chains may include: one or more processors 101, one or more input devices 102, one or more output devices 103, and memory 104, the processors 101, input devices 102, output devices 103, and memory 104 being interconnected via a bus 105. The memory 104 is used for storing a computer program comprising program instructions, and the processor 101 is configured for calling the program instructions to execute the method flow shown in fig. 1.
It should be understood that, in the embodiment of the present invention, the Processor 101 may be a Central Processing Unit (CPU), and the Processor may also be other general processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 102 may include a keyboard or the like, and the output device 103 may include a display (LCD or the like), a speaker, or the like.
The memory 104 may include read-only memory and random access memory, and provides instructions and data to the processor 101. A portion of the memory 104 may also include non-volatile random access memory. For example, the memory 104 may also store device type information.
The talent growth management terminal based on the block chain is implemented, a knowledge system database, a knowledge note comment database and a talent growth plan database are built based on the block chain technology, professional skill evaluation and talent resume metadata construction are carried out based on the databases, and a talent resume is built according to talent creation seed Hash and talent resume metadata; in the embodiment, metadata, knowledge note data, knowledge note comment data, professional skill assessment, talent resume and the like of a knowledge system are recorded on the block chain, talent management such as professional skill assessment, talent resume construction and the like is realized based on the block chain technology, and non-tamper-proof property and authority of data are ensured.
Those of ordinary skill in the art will appreciate that the algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described above generally in terms of their functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present application, it should be understood that the disclosed terminal and method can be implemented in other manners. For example, the above-described terminal embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A talent growth management method based on block chains is characterized by comprising the following steps:
constructing a knowledge system database, a knowledge note database and a knowledge note comment database based on a block chain technology;
performing professional skill evaluation on the individual according to the knowledge system database, the knowledge note database and the knowledge note evaluation database to obtain professional skill evaluation data;
constructing a talent growth plan database based on the block chain;
acquiring talent personal information data, and constructing talent resume metadata according to the talent personal information data, a talent growth plan database and occupational skill evaluation data;
constructing a talent resume according to the seed Hash of talent creation and the metadata of the talent resume;
wherein, constructing the talent growth plan database based on the blockchain comprises:
acquiring talent stage growth data, using talent growth seed Hash as talent growth creation Hash, wherein each talent has different talent growth plan data chains, the first element node Hash1 is talent growth creation Hash + first-stage metadata Hash, the second element node Hash2 is second-stage metadata Hash + first element node Hash1, the third element node Hash3 is third-stage metadata Hash + second-element node Hash2, and so on.
2. The method as claimed in claim 1, wherein the building of the knowledge-base database based on the blockchain technique comprises:
acquiring a discipline Hash, and taking the discipline Hash as discipline metadata;
building a discipline knowledge database according to the discipline metadata, wherein the discipline knowledge database comprises different disciplines, and the different disciplines comprise different versions and different step paths;
defining the Hash of each discipline element node as a knowledge system creation Hash of a corresponding knowledge system;
and constructing the knowledge system database according to the Hash created by the knowledge system and different advanced paths.
3. The method for talent growth management based on blockchain as claimed in claim 2, wherein building a discipline knowledge database based on the discipline metadata comprises:
the discipline meta-creation node Hash is discipline meta-data + discipline creation Hash, the second element node Hash4 is discipline Hash + discipline meta-creation node Hash, the third element node Hash5 is discipline Hash + second element node Hash4, and so on.
4. The block chain-based talent growth management method according to claim 2, wherein the constructing the knowledge-system database according to the knowledge-system creation Hash and different advanced paths specifically comprises:
the Hash is created by a first element node Hash6 which is a path first advanced knowledge system data Hash + knowledge system, a second element node Hash7 which is a path second advanced knowledge system data Hash + first element node Hash6, a third element node Hash8 which is a path third advanced knowledge system data Hash + second element node Hash7, and so on.
5. The method for talent growth management based on blockchain as claimed in claim 1, wherein building a knowledge note database based on blockchain technique comprises:
acquiring a knowledge note creation Hash and a note data Hash, wherein the knowledge note creation Hash is a meta-node Hash of each advanced knowledge system, and the note data Hash is knowledge note content;
constructing the knowledge note database according to the knowledge note creation Hash and the note data Hash, and specifically comprising the following steps:
the first meta node Hash9 is the note data Hash + knowledge note creation Hash, the second meta node Hash10 is the note data Hash + first meta node Hash9, the third meta node Hash11 is the note data Hash + second meta node Hash10, and so on.
6. The method for talent growth management based on blockchain as claimed in claim 1, wherein the building of the knowledge note review database based on blockchain technique comprises:
acquiring a knowledge note comment creation Hash and a note comment data Hash, wherein the knowledge note comment creation Hash is a Hash of each knowledge note meta node, and the note comment data Hash is knowledge note comment data;
constructing the knowledge note comment database according to the knowledge note comment creation Hash and the note comment data Hash, wherein the method specifically comprises the following steps:
the first element node Hash12 is the note evaluation data Hash + knowledge note evaluation creation Hash, the second element node Hash13 is the note evaluation data Hash + first element node Hash12, the third element node Hash14 is the note evaluation data Hash + second element node Hash13, and so on.
7. The blockchain-based talent growth management method of claim 1, further comprising:
and building a knowledge note and a learning record of a knowledge system based on the block chain.
8. The method as claimed in claim 7, wherein the building of knowledge notes based on blockchains comprises:
acquiring professional evaluation knowledge note creation Hash and note metadata Hash, wherein the professional evaluation knowledge note creation Hash is metadata for each professional skill evaluation, the metadata for each professional skill evaluation is obtained according to a knowledge system database, a knowledge note database and a knowledge note comment database, and the note metadata Hash is knowledge note content;
constructing a knowledge note according to the occupational evaluation knowledge note creation Hash and the note metadata Hash, and specifically comprising the following steps:
the first meta node Hash15 is the note metadata Hash + occupation assessment knowledge note creation Hash, the second meta node Hash16 is the note metadata Hash + first meta node Hash15, the third node Hash17 is the note metadata Hash + second node Hash16, and so on.
9. The method according to claim 7, wherein the building of the learning record of the knowledge system based on the blockchain comprises:
acquiring a knowledge Hash of first learning and a new knowledge system Hash;
establishing a learning record of the knowledge system according to the knowledge Hash learned for the first time and the new knowledge system Hash, which specifically comprises the following steps:
taking the knowledge Hash learned for the first time as a first element node Hash18, taking a second element node Hash19 as a new knowledge system Hash + a first element node Hash18, taking a third element node Hash20 as a new knowledge system Hash + a second element node Hash19, and so on.
10. A talent growth management terminal based on a blockchain, comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is configured to store a computer program comprising program instructions, and the processor is configured to invoke the program instructions to perform the method according to any one of claims 1 to 9.
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